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Wi-Fi Network Intrusion Detection: Enhanced with Feature Extraction and Machine Learning Algorithms

Category: Mini Projects

Price: ₹ 4500 ₹ 10000 55% OFF

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Wireless Fidelity (Wi-Fi) is one of the most widely used technologies for wireless internet access, enabling users to connect devices without the need for physical cables. With the growing number of devices connected to Wi-Fi networks, especially in environments like schools, offices, and smart homes, the need for secure and efficient network management has become critical. Wi-Fi plays a pivotal role in enabling the Internet of Things (IoT), which connects various smart devices to the internet, offering greater convenience and efficiency. However, the same connectivity that makes Wi-Fi so convenient also exposes it to a variety of vulnerabilities, making it susceptible to network attacks and unauthorized access.
The risks associated with Wi-Fi networks can range from reduced service quality due to unauthorized use, to serious security breaches such as personal data theft. These attacks can be executed in many ways, including through man-in-the-middle attacks, denial-of-service attacks, or by exploiting weak encryption methods. As such, safeguarding Wi-Fi networks against these threats is essential. This is where network intrusion detection systems (NIDS) come into play. NIDS are designed to monitor network traffic for signs of suspicious activity or potential breaches, alerting administrators to take necessary actions before a network compromise occurs.

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